[BioC] GSEA with one class metaanalysis

[Mark W Kimpel]

I am in the process of performing a meta-analysis on multiple MA studies 
run on several platforms and several species. Although I realize there 
are probably other ways to approach the data, my collaborators have 
chosen to use Cohen's D-statistic to summarize their data.

I would like to use GSEA to look for over-represented groups or pathways 
in the data, but what I will end up with is essentially a one-class 
experiment. In other words, I would like to identify groups whose 
summary D-statistic (I recognize from the recent literature that there 
is more than one summary method available) is different from zero.

 From what I have read, the GSEA method is usually used to evaluate 2 
class data, the GSA method of Tibshurani can be used to evaluate 
multi-class data, but can either method be easily adapted to evaluate 
one class data? It would seem theoretically reasonable, but I don't know 
if I would have to modify one of the packages or if one already provides 
for this.

And, while I'm at it, I will also want to look for individual genes 
whose average D-statistic is different from zero. I am advocating using 
a t-test with n=number of experiments with corresponding degrees of 
freedom, whereas others are advocating using a z-test because the 
D-statistics are summarizing many underlying individual statistics.

Help with these questions would be deeply appreciated.

Mark

-- 
Mark W. Kimpel MD
Neuroinformatics
Department of Psychiatry
Indiana University School of Medicine